Abstract
A two-way coupling of the operational mesoscale weather prediction model known as Lokal Modell (LM; German Weather Service) with the land surface hydrologic “TOPMODEL”-Based Land Surface–Atmosphere Transfer Scheme (TOPLATS; Princeton University) has been carried out to investigate the influence of a “state-of-the-art” land surface hydrologic model on the predicted local weather. Two case studies are presented that quantify the influence of the combined modeling system on the turbulent fluxes and boundary layer structure and on the formation of precipitation. The model results are compared with ground-based measurements of turbulent fluxes, boundary layer structure, and precipitation. Furthermore, whether the initialization of the original LM with more realistic soil moisture fields would be sufficient to improve the weather forecast is investigated. The results of the two case studies show that, when compared with measurements, the two-way coupled modeling system using TOPLATS improves the predicted energy fluxes and rain amount in comparison with predictions from the original LM. The initialization of the LM just using soil moisture fields based on TOPLATS does not result in an improvement of the local weather forecast: although the simulation of the sensible and latent heat fluxes is improved, the representation of the boundary layer structure is not captured well. In the original LM, the surface processes are not modeled in sufficient detail, which resulted in significant overprediction of precipitation for one case study. The main reason for the improved performance of the two-way coupled modeling system on the basis of TOPLATS probably is the more accurate representation of vegetation and soil hydrologic processes. This results in more realistically simulated soil moisture fields and better simulation of the dynamic range of the surface temperature when compared with the other model configurations.
Corresponding author address: G. Seuffert, European Centre for Medium-Range Weather Forecasts, Shinfield Park, Reading RG2 9AX, United Kingdom. Email: g.seuffert@ecmwf.int
